Doctors at central Ohio’s major hospital systems say artificial intelligence is helping them see more than they could before.

Abstract: This paper presents an optimized lightweight Super-Resolution Convolutional Neural Network (SRCNN) capable of reconstructing high-quality images with strong fidelity. The proposed framework ...

Abstract: We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented ...

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...

A new imaging technique turns motion blur into an advantage, using a jiggling camera and a clever algorithm to create super-resolution images sharper than would be possible with a steady camera.